Published on February 25, 2026, this roughly 22-minute tutorial discusses inference and training for diffusion language models (dLLMs).
The technical tutorial, published on February 25, 2026, runs for about 22 minutes and covers dLLM inference and training. Topics include self-distillation to reduce diffusion steps, curriculum learning, an LLM verifier, and KV cache.
The material presents techniques relevant to people exploring dLLMs; its description gives no quantitative results. To verify the scope and details, consult the original tutorial and compare each claim with its contents, without assuming results beyond those described.